Sentiment Classification of Visitors in Yogyakarta Palace using Support Vector Machine
Cahva Damariati, Fadia Rani, Slamet Riyadi, Gan Kok Beng · 2022 Seventh International Conference on Informatics and Computing (ICIC) · 2022
Yogyakarta is one of Indonesia's most popular tourist destinations with its Yogyakarta Palace “Keraton”. Trip Advisor, one of the most extensive traveller guides, provides visitor reviews about the Keraton. Since the review is very important for Keraton management and was not analyzed yet, this research aims to classify the visitor sentiment on Keraton using the Support Vector Machine (SVM) method. The research method involved collecting comments from the website, preprocessing, including data cleaning, tokenizing, transforming, and stopwords filtering, as well as classifying the sentiment as positive and negative. This study showed that the SVM could classify the sentiment with 75.79% accuracy.